Eur. Phys. J. Spec. Top. (2022) 231: 2439-2443
https://doi.org/10.1140/epjs/s11734-022-00478-w

Regular Article

Effect of Noise variance in spiral wave suppression for a multi-layered neuron model with flux coupling modelled using a memristor

¹ Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, India
² Department of Electronics and Communication Engineering, Prathyusha Engineering College, 602025, Chennai, India

Received: 29 October 2021
Accepted: 16 February 2022
Published online: 2 March 2022

Abstract

Dynamics of multi-layered neuronal network are challenging and spiral wave suppression is vital particularly in biological systems such as cortical tissue in brain, heart muscles etc., In this study, one-, two- and three-layer neuronal network of an exponential flux memristor-based Morris-Lecar neuron model subjected to low-frequency electromagnetic field (MLELF) is considered and the influence of noise variance in spiral wave suppression is investigated. A Box- Muller type Gaussian noise is used as stimulation and the influence of noise variance on neuronal network is studied. The results exposed the multilayer neuronal network influenced much by a very low noise variance on spiral wave suppression while compared with the single-layer network. As increase in noise variance, the dynamics of the spiral wave changes significantly and ended with turbulence. The study highlighted the spiral waves can be potentially suppressed even the network is under higher frequency external electric field using noise variance.